loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Chunbo Song and Christopher Rasmussen

Affiliation: Department of Computer and Information Science, University of Delaware, Newark, DE, U.S.A.

Keyword(s): Tracking, Detection, Video Analysis.

Abstract: We present a deep learning approach to sports video understanding as part of the development of an automated refereeing system for broadcast soccer games. The task of identifying which players are involved in a foul at a given moment is one of spatiotemporal action recognition in a cluttered visual environment. We describe how to employ multi-object tracking to generate a base set of candidate image sequences which are post-processed to mitigate common mistracking scenarios and then classified according to several two-person interaction types. For this work we created a large soccer foul dataset with a significant video component for training relevant networks. Our system can differentiate foul participants from bystanders with high accuracy and localize them over a wide range of game situations. We also report reasonable accuracy for distinguishing the player who committed the foul, or subject, from the object of the infraction, despite very low-resolution images.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.15.202.4

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Song, C. and Rasmussen, C. (2022). Who Did It? Identifying Foul Subjects and Objects in Broadcast Soccer Videos. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 5: VISAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 48-54. DOI: 10.5220/0010770600003124

@conference{visapp22,
author={Chunbo Song. and Christopher Rasmussen.},
title={Who Did It? Identifying Foul Subjects and Objects in Broadcast Soccer Videos},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 5: VISAPP},
year={2022},
pages={48-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010770600003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 5: VISAPP
TI - Who Did It? Identifying Foul Subjects and Objects in Broadcast Soccer Videos
SN - 978-989-758-555-5
IS - 2184-4321
AU - Song, C.
AU - Rasmussen, C.
PY - 2022
SP - 48
EP - 54
DO - 10.5220/0010770600003124
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic